The role of acoustics in defining killer whale populations and societies in the Northeastern Pacific Ocean.
Bibliographic record
Abstract
Stable, culturally inherited repertoires of discrete pulsed calls are characteristic of the acoustic behavior of killer whales. Call repertoires may have important roles in the evolution of social segregation and reproductive isolation of sympatric killer whale populations. Here we present the results of analyzes of recordings collected from killer whale populations in coastal waters of the Northeastern Pacific from the Aleutian Islands to the Gulf of California over the past 30 years. At least three acoustically, genetically, and ecologically distinct lineages of killer whales, known as residents, transients, and offshores, inhabit these waters. Call repertoires within these lineages can further distinguish populations, communities, or smaller social groups, depending on social structure and patterns of dispersal. Salmon-feeding residents live permanently in their natal matrilines and have group-specific dialects that encode maternal genealogy. Mammal-feeding transient groups have less stable societies and tend not to have group-specific dialects, though there are regional call differences among subpopulations. Offshore killer whales, which range widely along the continental shelf and may specialize on sharks, have distinct call repertoires that appear to vary among groups. Killer whale calls can provide important insights into the structure of populations at a scale that cannot be resolved through genetic studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".